Functional regulation of PVBV Nuclear Inclusion protein-a protease activity upon interaction with Viral Protein genome-linked and phosphorylation

Regulation of NIa-Pro is crucial for polyprotein processing and hence, for successful infection of potyviruses. We have examined two novel mechanisms that could regulate NIa-Pro activity. Firstly, the influence of VPg domain on the proteolytic activity of NIa-Pro was investigated. It was shown that the turnover number of the protease increases when these two domains interact (as: two-fold; trans: seven-fold) with each other. Secondly, the protease activity of NIa-Pro could also be modulated by phosphorylation at Ser129. A mutation of this residue either to aspartate (phosphorylation-mimic) or alanine (phosphorylation-deficient) drastically reduces the protease activity. Based on these observations and molecular modeling studies, we propose that interaction with VPg as well as phosphorylation of Ser129 could relay a signal through Trp143 present at the protein surface to the active site pocket by subtle conformational changes, thus modulating protease activity of NIa-Pro. (C) 2011 Elsevier Inc. All rights reserved.

Computational Biology and Language

Current scientific research is characterized by increasing specialization, accumulating knowledge at a high speed due to parallel advances in a multitude of sub-disciplines. Recent estimates suggest that human knowledge doubles every two to three years – and with the advances in information and communication technologies, this wide body of scientific knowledge is available to anyone, anywhere, anytime. This may also be referred to as ambient intelligence – an environment characterized by plentiful and available knowledge. The bottleneck in utilizing this knowledge for specific applications is not accessing but assimilating the information and transforming it to suit the needs for a specific application. The increasingly specialized areas of scientific research often have the common goal of converting data into insight allowing the identification of solutions to scientific problems. Due to this common goal, there are strong parallels between different areas of applications that can be exploited and used to cross-fertilize different disciplines. For example, the same fundamental statistical methods are used extensively in speech and language processing, in materials science applications, in visual processing and in biomedicine. Each sub-discipline has found its own specialized methodologies making these statistical methods successful to the given application. The unification of specialized areas is possible because many different problems can share strong analogies, making the theories developed for one problem applicable to other areas of research. It is the goal of this paper to demonstrate the utility of merging two disparate areas of applications to advance scientific research. The merging process requires cross-disciplinary collaboration to allow maximal exploitation of advances in one sub-discipline for that of another. We will demonstrate this general concept with the specific example of merging language technologies and computational biology.

Language identification using parallel sub-word recognition

Parallel sub-word recognition (PSWR) is a new model that has been proposed for language identification (LID) which does not need elaborate phonetic labeling of the speech data in a foreign language. The new approach performs a front-end tokenization in terms of sub-word units which are designed by automatic segmentation, segment clustering and segment HMM modeling. We develop PSWR based LID in a framework similar to the parallel phone recognition (PPR) approach in the literature. This includes a front-end tokenizer and a back-end language model, for each language to be identified. Considering various combinations of the statistical evaluation scores, it is found that PSWR can perform as well as PPR, even with broad acoustic sub-word tokenization, thus making it an efficient alternative to the PPR system.

Functional characterization of UvrD helicases from Haemophilus influenzae and Helicobacter pylori

Haemophilus influenzae and Helicobacter pylori are major bacterial pathogens that face high levels of genotoxic stress within their host. UvrD, a ubiquitous bacterial helicase that plays important roles in multiple DNA metabolic pathways, is essential for genome stability and might, therefore, be crucial in bacterial physiology and pathogenesis. In this study, the functional characterization of UvrD helicase from Haemophilus influenzae and Helicobacter pylori is reported. UvrD from Haemophilus influenzae (HiUvrD) and Helicobacter pylori (HpUvrD) exhibit strong single-stranded DNA-specific ATPase and 3'5' helicase activities. Mutation of highly conserved arginine (R288) in HiUvrD and glutamate (E206) in HpUvrD abrogated their activities. Both the proteins were able to bind and unwind a variety of DNA structures including duplexes with strand discontinuities and branches, three- and four-way junctions that underpin their role in DNA replication, repair and recombination. HiUvrD required a minimum of 12 nucleotides, whereas HpUvrD preferred 20 or more nucleotides of 3'-single-stranded DNA tail for efficient unwinding of duplex DNA. Interestingly, HpUvrD was able to hydrolyze and utilize GTP for its helicase activity although not as effectively as ATP, which has not been reported to date for UvrD characterized from other organisms. HiUvrD and HpUvrD were found to exist predominantly as monomers in solution together with multimeric forms. Noticeably, deletion of distal C-terminal 48 amino acid residues disrupted the oligomerization of HiUvrD, whereas deletion of 63 amino acids from C-terminus of HpUvrD had no effect on its oligomerization. This study presents the characteristic features and comparative analysis of Haemophilus influenzae and Helicobacter pylori UvrD, and constitutes the basis for understanding the role of UvrD in the biology and virulence of these pathogens.

Dual functional performance of fiber Bragg gratings coated with metals using flash evaporation technique

Metallic and other type of coatings on fiber Bragg grating (FBG) sensors alter their sensitivity with thermal and mechanical stress while protecting the fragile optical fiber in harsh sensing surroundings. The behavior of the coated materials is unique in their response to thermal and mechanical stress depending on the thickness and the mode of coating. The thermal stress during the coating affects the temperature sensitivity of FBG sensors. We have explored the thermal response of FBGs coated with Al and Pb to an average thickness of 80 nm using flash evaporation technique where the FBG sensor is mounted in a region at room temperature in an evacuated chamber having a pressure of 10(6) Torr which will minimize any thermal stress during the coating process. The coating thickness is chosen in the nanometer region with the aim to study thermal behavior of nanocoatings and their effect on FBG sensitivity. The sensitivity of FBGs is evaluated from the wavelengths recorded using an optical sensing interrogator sm 130 (Micron Optics) from room temperature to 300 degrees C both during heating and cooling. It is observed that the sensitivity of the metal coated fibers is better than the reference FBG with no coating for the entire range of temperature. For a coating thickness of 80 nm, Al coated FBG is more sensitive than the one coated with Pb up to 170 degrees C and it reverses at higher temperatures. This point is identified as a reversible phase transition in Pb monolayers as the 2-dimensional aspects of the metal layers are dominant in the nanocoatings of Pb. On cooling, the phase transition reverses and the FBGs return to the original state and for repeated cycles of heating and cooling the same pattern is observed. Thus the FBG functions as a sensor of the phase transitions of the coatings also. (C) 2012 Elsevier Inc. All rights reserved.

Functional Analysis of the Genes Encoding Diaminopropionate Ammonia Lyase in Escherichia coli and Salmonella enterica Serovar Typhimurium

Diaminopropionate ammonia lyase (DAPAL) is a pyridoxal-5'phosphate (PLP)-dependent enzyme that catalyzes the conversion of diaminopropionate (DAP) to pyruvate and ammonia and plays an important role in cell metabolism. We have investigated the role of the ygeX gene of Escherichia coli K-12 and its ortholog, STM1002, in Salmonella enterica serovar Typhimurium LT2, presumed to encode DAPAL, in the growth kinetics of the bacteria. While Salmonella Typhimurium LT2 could grow on DL-DAP as a sole carbon source, the wild-type E. coli K-12 strain exhibited only marginal growth on DL-DAP, suggesting that DAPAL is functional in S. Typhimurium. The expression of ygeX in E. coli was low as detected by reverse transcriptase PCR (RT-PCR), consistent with the poor growth of E. coli on DL-DAP. Strains of S. Typhimurium and E. coli with STM1002 and ygeX, respectively, deleted showed loss of growth on DL-DAP, confirming that STM1002 (ygeX) is the locus encoding DAPAL. Interestingly, the presence of DL-DAP caused a growth inhibition of the wild-type E. coli strain as well as the knockout strains of S. Typhimurium and E. coli in minimal glucose/glycerol medium. Inhibition by DL-DAP was rescued by transforming the strains with plasmids containing the STM1002 (ygeX) gene encoding DAPAL or supplementing the medium with Casamino Acids. Growth restoration studies using media lacking specific amino acid supplements suggested that growth inhibition by DL-DAP in the absence of DAPAL is associated with auxotrophy related to the inhibition of the enzymes involved in the biosynthetic pathways of pyruvate and aspartate and the amino acids derived from them.

Suite of tools for statistical N-gram language modeling for pattern mining in whole genome sequences

Genome sequences contain a number of patterns that have biomedical significance. Repetitive sequences of various kinds are a primary component of most of the genomic sequence patterns. We extended the suffix-array based Biological Language Modeling Toolkit to compute n-gram frequencies as well as n-gram language-model based perplexity in windows over the whole genome sequence to find biologically relevant patterns. We present the suite of tools and their application for analysis on whole human genome sequence.

Adsorption on Edge-Functionalized Bilayer Graphene Nanoribbons: Assessing the Role of Functional Groups in Methane Uptake

A combination of ab initio and classical Monte Carlo simulations is used to investigate the effects of functional groups on methane binding. Using Moller-Plesset (MP2) calculations, we obtain the binding energies for benzene functionalized with NH2, OH, CH3, COOH, and H2PO3 and identify the methane binding sites. In all cases, the preferred binding sites are located above the benzene plane in the vicinity of the benzene carbon atom attached to the functional group. Functional groups enhance methane binding relative to benzene (-6.39 kJ/mol), with the largest enhancement observed for H2PO3 (-8.37 kJ/mol) followed by COOH and CH3 (-7.77 kJ/mol). Adsorption isotherms are obtained for edge-functionalized bilayer graphene nanoribbons using grand canonical Monte Carlo simulations with a five-site methane model. Adsorbed excess and heats of adsorption for pressures up to 40 bar and 298 K are obtained with functional group concentrations ranging from 3.125 to 6.25 mol 96 for graphene edges functionalized with OH, NH2, and COOH. The functional groups are found to act as preferred adsorption sites, and in the case of COOH the local methane density in the vicinity of the functional group is found to exceed that of bare graphene. The largest enhancement of 44.5% in the methane excess adsorbed is observed for COOH-functionalized nanoribbons when compared to H terminated ribbons. The corresponding enhancements for OH- and NH2-functionalized ribbons are 10.5% and 3.7%, respectively. The excess adsorption across functional groups reflects the trends observed in the binding energies from MP2 calculations. Our study reveals that specific site functionalization can have a significant effect on the local adsorption characteristics and can be used as a design strategy to tailor materials with enhanced methane storage capacity.

Functional maps within a single neuron

Narayanan R, Johnston D. Functional maps within a single neuron. J Neurophysiol 108: 2343-2351, 2012. First published August 29, 2012; doi:10.1152/jn.00530.2012.-The presence and plasticity of dendritic ion channels are well established. However, the literature is divided on what specific roles these dendritic ion channels play in neuronal information processing, and there is no consensus on why neuronal dendrites should express diverse ion channels with different expression profiles. In this review, we present a case for viewing dendritic information processing through the lens of the sensory map literature, where functional gradients within neurons are considered as maps on the neuronal topograph. Under such a framework, drawing analogies from the sensory map literature, we postulate that the formation of intraneuronal functional maps is driven by the twin objectives of efficiently encoding inputs that impinge along different dendritic locations and of retaining homeostasis in the face of changes that are required in the coding process. In arriving at this postulate, we relate intraneuronal map physiology to the vast literature on sensory maps and argue that such a metaphorical association provides a fresh conceptual framework for analyzing and understanding single-neuron information encoding. We also describe instances where the metaphor presents specific directions for research on intraneuronal maps, derived from analogous pursuits in the sensory map literature. We suggest that this perspective offers a thesis for why neurons should express and alter ion channels in their dendrites and provides a framework under which active dendrites could be related to neural coding, learning theory, and homeostasis.

Design and Synthesis of a Functional Derivative of the Triazinium Cation and Its Rhodium Complex that Shows Photoinduced DNA Cleavage Activity and Photocytotoxicity

The design and synthesis of an intensely blue rhodium(III) complex 3]+ of a new N,N-donor ligand, 8-(quinolin-8-ylamino)pyrido2,1-c]1,2,4]benzotriazin-11-ium, 2]+, which contains a planar pendant triazinium arm, is described. Structural characterization for 3]+ was carried out by using various spectroscopic techniques and single-crystal X-ray crystallography. The organometallic rhodium(III) compound shows a ligand-based reversible reduction at 0.65 V. The electrochemically reduced compound displays a single-line EPR spectrum that signifies the formation of ligand-based free radicals. Compound 3]+ shows a binding propensity to calf thymus DNA to give a Kapp value of 6.05X105 M1. The parent triazinium salt, pyrido2,1-c]1,2,4]benzotriazin-11-ium 1]+ and the ligand salt 2]+ exhibit photoinduced cleavage of DNA in UV-A light, whereas the reference Rh complex 3]+ photocleaves DNA with red light (647.1 nm). The compounds show photonuclease activities under both aerobic and anaerobic conditions. Mechanistic investigations under aerobic conditions with several inhibitors indicate the formation of hydroxyl radicals by means of a photoredox pathway. Under anaerobic conditions, it is believed that a photoinduced oxidation of DNA mechanism is operative. Compound 3]+ exhibits photocytotoxicity in HeLa cervical cancer cells to give IC50 values of (12+/-0.9) mu M in UV-A light at 365 nm and (31.4+/-1.1) mu M in the dark.

Vaporization dynamics of functional droplets in a hot laminar air jet

The vaporization characteristics of pendant droplets of various chemical compositions (like conventional fuels, alternative fuels and nanosuspensions) subjected to convective heating in a laminar air jet have been analyzed. Different heating conditions were achieved by controlling the air temperature and velocity fields around the droplet. A hybrid timescale has been proposed which incorporates the effects of latent heat of vaporization, saturation vapor pressure and thermal diffusivity. This timescale in essence encapsulates the different parameters that influence the droplet vaporization rate. The analysis further permits the evaluation of the effect of various parameters such as surrounding temperature, Reynolds number, far-field vapor presence, impurity content and agglomeration dynamics (nanosuspensions) in the droplet. Flow visualization has been carried out to understand the role of internal recirculation on the vaporization rate. The visualization indicates the presence of a single vortex cell within the droplet on account of the rotation and oscillation of the droplet due to aerodynamic load. External heating induced agglomeration in nanofluids leads to morphological changes during the vaporization process. These morphological changes and alteration in vaporization behavior have been assessed using high speed imaging of the diameter regression and Scanning Electron Microscopy images of the resultant precipitate. (C) 2012 Elsevier Ltd. All rights reserved.

q-Gaussian based Smoothed Functional Algorithms for Stochastic Optimization

The q-Gaussian distribution results from maximizing certain generalizations of Shannon entropy under some constraints. The importance of q-Gaussian distributions stems from the fact that they exhibit power-law behavior, and also generalize Gaussian distributions. In this paper, we propose a Smoothed Functional (SF) scheme for gradient estimation using q-Gaussian distribution, and also propose an algorithm for optimization based on the above scheme. Convergence results of the algorithm are presented. Performance of the proposed algorithm is shown by simulation results on a queuing model.